Incident Score: Analysis & Impact (COU1767939226)
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Rankiteo Score Impact Analysis
Key Highlights From The Incident Analysis
- Timeline of Coupang's Breach and lateral movement inside company's environment.
- Overview of affected data sets, including SSNs and PHI, and why they materially increase incident severity.
- How Rankiteo’s incident engine converts technical details into a normalized incident score.
- How this cyber incident impacts Coupang Rankiteo cyber scoring and cyber rating.
- Rankiteo’s MITRE ATT&CK correlation analysis for this incident, with associated confidence level.
Full Incident Analysis Transcript
In this Rankiteo incident briefing, we review the Coupang breach identified under incident ID COU1767939226.
The analysis begins with a detailed overview of Coupang's information like the linkedin page: https://www.linkedin.com/company/coupang, the number of followers: 242085, the industry type: Software Development and the number of employees: 8652 employees
After the initial compromise, the video explains how Rankiteo's incident engine converts technical details into a normalized incident score. The incident score before the incident was 100 and after the incident was 100 with a difference of 0 which is could be a good indicator of the severity and impact of the incident.
In the next step of the video, we will analyze in more details the incident and the impact it had on Coupang and their customers.
Coupang recently reported "Coupang-Related Voice Phishing Scams Exploiting Personal Data Leaks", a noteworthy cybersecurity incident.
Criminals are exploiting anxiety over personal data leaks at Coupang to conduct voice phishing scams, including fake credit card delivery schemes and malicious links under the guise of compensation or delivery delays.
The disruption is felt across the environment, and exposing Personal data (names, phone numbers, bank account details), plus an estimated financial loss of No confirmed financial losses reported.
Formal response steps have not been shared publicly yet.
The case underscores how Ongoing (closer monitoring by FSS and police), teams are taking away lessons such as Users must verify unexpected calls or messages, especially those requesting personal or financial information. Companies should enhance customer education on phishing risks and improve data protection measures to prevent leaks, and recommending next steps like Implement multi-factor authentication for customer accounts, Enhance customer education on phishing and social engineering risks and Strengthen data protection measures to prevent leaks, with advisories going out to stakeholders covering Coupang users advised to verify unexpected calls or messages and avoid clicking on suspicious links.
Finally, we try to match the incident with the MITRE ATT&CK framework to see if there is any correlation between the incident and the MITRE ATT&CK framework.
The MITRE ATT&CK framework is a knowledge base of techniques and sub-techniques that are used to describe the tactics and procedures of cyber adversaries. It is a powerful tool for understanding the threat landscape and for developing effective defense strategies.
MITRE ATT&CK® Correlation Analysis
Rankiteo's analysis has identified several MITRE ATT&CK tactics and techniques associated with this incident, each with varying levels of confidence based on available evidence. Under the Initial Access tactic, the analysis identified Phishing: Voice Phishing (Vishing) (T1566.004) with high confidence (90%), supported by evidence indicating victims report receiving calls from scammers posing as delivery personnel or customer service and Phishing: Spearphishing Link (T1566.001) with moderate to high confidence (80%), supported by evidence indicating malicious links disguised as delivery updates. Under the Credential Access tactic, the analysis identified Gather Victim Identity Information: Credentials (T1589.001) with high confidence (90%), supported by evidence indicating scammers...armed with personal details—including names, phone numbers, and partial bank account information and Gather Victim Identity Information: Email Addresses (T1589.002) with moderate to high confidence (70%), supported by evidence indicating personal data reused from past breaches. Under the Reconnaissance tactic, the analysis identified Phishing for Information: Spearphishing for Information (T1598.003) with moderate to high confidence (80%), supported by evidence indicating scammers reuse personal data from past breaches to craft convincing scenarios. Under the Resource Development tactic, the analysis identified Obtain Capabilities: Tool (T1588.002) with moderate to high confidence (70%), supported by evidence indicating fake customer service line (beginning with 1544). Under the Execution tactic, the analysis identified User Execution: Malicious Link (T1204.001) with moderate to high confidence (80%), supported by evidence indicating malicious links disguised as delivery updates. Under the Impact tactic, the analysis identified Defacement: Internal Defacement (T1491.001) with moderate confidence (60%), supported by evidence indicating negative impact on Coupangs brand reputation due to perceived data leaks. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.
Sources & References
- Coupang Rankiteo Cyber Incident Details: https://www.rankiteo.com/company/coupang/incident/COU1767939226
- Coupang CyberSecurity Rating page: https://www.rankiteo.com/company/coupang
- Coupang Rankiteo Cyber Incident Blog Article: https://blog.rankiteo.com/cou1767939226-coupang-breach-january-2026/
- Coupang CyberSecurity Score History: https://www.rankiteo.com/company/coupang/history
- Coupang CyberSecurity Incident Source: https://www.koreatimes.co.kr/business/banking-finance/20260109/coupang-customers-on-alert-over-phishing-attempts-after-data-breach
- Rankiteo A.I CyberSecurity Rating methodology: https://www.rankiteo.com/Images/rankiteo_algo.pdf
- Rankiteo TPRM Scoring methodology: https://static.rankiteo.com/model/rankiteo_tprm_methodology.pdf